Search results for "Artificial Intelligence"

Efficient Protection for VDI Workstations

2019

Many enterprises migrate to a private cloud VDI environment. In such an environment multiple workstations are served by a single powerful server. On such an environment each VDI workstation receives only a limited CPU power. An average of less than a quarter of a core per planned VDI workstation is a common setup. Under such cases, anti-virus and application control software load is multiplied by the number of VDI workstation running on each server. These security applications take merely a few percentages of a single core on a normal desktop. However, on a VDI server where the multiple VDI workstations run on a single server, they may consume 20-25 percent the load. Naturally, such an incr…

Serious Game Design for Flooding Triggered by Extreme Weather

2017

Managing crises with limited resources through a serious game is deemed as one of the ways of training and can be regarded as an alternative to a table-top exercise. This article presents the so-called “Operasjon Tyrsdal” serious game, inspired by a real case of extreme weather that hit the west coast of Norway. This reference case is used to add realism to the game. The game is designed for a single player, while the mechanics are framed in such a way that the player will have limited resources, and elevated event pressure over time. Beside applying an iterative Scrum method with seven Sprint cycles, we combined the development work with desk research and used the involvement of testers, i…

A Novel Intelligent Technique for Product Acceptance Process Optimization on the Basis of Misclassification Probability in the Case of Log-Location-S…

2019

In this paper, to determine the optimal parameters of the product acceptance process under parametric uncertainty of underlying models, a new intelligent technique for optimization of product acceptance process on the basis of misclassification probability is proposed. It allows one to take into account all possible situations that may occur when it is necessary to optimize the product acceptance process. The technique is based on the pivotal quantity averaging approach (PQAA) which allows one to eliminate the unknown parameters from the problem and to use available statistical information as completely as possible. It is conceptually simple and easy to use. One of the most important featur…

Proper Incentives for Proper IT Security Management _ A System Dynamics Approach

2017

Automated Dental Identification with Lowest Cost Path-Based Teeth and Jaw Separation

2016

Abstract Teeth are some of the most resilient tissues of the human body. Because of their placement, teeth often yield intact indicators even when other metrics, such as finger prints and DNA, are missing. Forensics on dental identification is now mostly manual work which is time and resource intensive. Systems for automated human identification from dental X-ray images have the potential to greatly reduce the necessary efforts spent on dental identification, but it requires a system with high stability and accuracy so that the results can be trusted. This paper proposes a new system for automated dental X-ray identification. The scheme extracts tooth and dental work contours from the X-ray…

Intelligent Constructing Exact Tolerance Limits for Prediction of Future Outcomes Under Parametric Uncertainty

2021

The problem of constructing one-sided exact statistical tolerance limits on the kth order statistic in a future sample of m observations from a distribution of log-location-scale family on the basis of an observed sample from the same distribution is considered. The new technique proposed here emphasizes pivotal quantities relevant for obtaining tolerance factors and is applicable whenever the statistical problem is invariant under a group of transformations that acts transitively on the parameter space. The exact tolerance limits on order statistics associated with sampling from underlying distributions can be found easily and quickly making tables, simulation, Monte Carlo estimated percen…

A New Intelligent Technique of Constructing Optimal Airline Seat Protection Levels for Multiple Nested Fare Classes of Single-Leg Flights

2019

A new, rigorous formulation of the optimization problem of airline seat protection levels for multiple nested fare classes is presented. A number of results useful for practical application are obtained. A numerical example is given.

Data Sources Handling for Emergency Management: Supporting Information Availability and Accessibility for Emergency Responders

2017

Information is an essential component for better emergency response. Although a lot of information being available at various places during any kind of emergency, many emergency responders (ERs) use only a limited amount of the available information. The reason for this is that the available information heterogeneously distributed, in different formats, and ERs are unable to get access to the relevant information. Moreover, without having access to the needed information, many emergency responders are not able to obtain a sufficient understanding of the emergency situation. Consequently, a lot of time is being used to search for the needed information and poor decisions may be made. Therefo…

Deep in the Dark: A Novel Threat Detection System using Darknet Traffic

2019

This paper proposes a threat detection system based on Machine Learning classifiers that are trained using darknet traffic. Traffic destined to Darknet is either malicious or by misconfiguration. Darknet traffic contains traces of several threats such as DDoS attacks, botnets, spoofing, probes and scanning attacks. We analyse darknet traffic by extracting network traffic features from it that help in finding patterns of these advanced threats. We collected the darknet traffic from the network sensors deployed at SURFnet and extracted several network-based features. In this study, we proposed a framework that uses supervised machine learning and a concept drift detector. Our experimental res…

The regression Tsetlin machine: a novel approach to interpretable nonlinear regression

2019

Relying simply on bitwise operators, the recently introduced Tsetlin machine (TM) has provided competitive pattern classification accuracy in several benchmarks, including text understanding. In this paper, we introduce the regression Tsetlin machine (RTM), a new class of TMs designed for continuous input and output, targeting nonlinear regression problems. In all brevity, we convert continuous input into a binary representation based on thresholding, and transform the propositional formula formed by the TM into an aggregated continuous output. Our empirical comparison of the RTM with state-of-the-art regression techniques reveals either superior or on par performance on five datasets. Thi…